Planning tools are widely used in the petrochemical industry to assist in the planning of activities in a refinery. Among the planning tools widely used in the petrochemical industry are PIMS by AspenTech, RPMS by Honeywell, and GRTMPS by Haverly Systems. The models used in these tools are typically composed of:                raw material (e.g. crude oil) supply data, including quantities and prices,        raw material characterization data,        product (e.g. gasoline, diesel) demand data, including quantities and prices,        process models which represent the production facilities,        product blending models which represent the blending facilities and specifications, and        other constraints.        
These planning tools can be used as decision support aids for raw material purchases, refinery operations, product sales, or other planning decisions. Traditionally, raw material purchase and product sales decisions are made on the basis of a planning optimization model that represents the time horizon as one period with average conditions being assumed throughout each period (i.e. period-average models). The task of developing the raw material delivery schedule and the production schedule are predominantly separate activities which are finalized after the period average plan for raw material purchases and production has been developed. Given these purchases and sales decisions, more detailed production planning and/or production scheduling are performed as subsequent steps. Ideally, a feasible production schedule would be developed that is consistent and equivalent to the planning model result. In practice, however, the process operation is not uniform over the time horizon and a planning model which assumes this to be true often leads to a planning result which cannot be converted into an equivalent schedule.
A simulation model may be used to support the development of a production schedule. The production schedule may include changes in various process operations which are scheduled to start and end at certain times during the time horizon. Raw material deliveries and product shipments are to be scheduled such that these are consistent and feasible with the production schedule. Often, transportation costs are significant and the minimization of transportation costs is important. Inventory dynamics within each period are not considered in the production planning activity since the plan is performed with a period average view of the production. However, inventory and the fluctuation of material inventory levels within each period can be important in the production schedule. Typically, the production scheduling activity seeks to find a feasible schedule which matches the production plan, where feasibility includes keeping inventory levels within the allowed range (minimum and maximum levels) at all times during the time horizon. An additional objective is to minimize the inventory holding costs (i.e. minimize capital costs).
Scheduling tools may be used to obtain a feasible schedule for raw material delivery, production, and product shipments. Examples of such production scheduling tools are ORION by AspenTech, Production Scheduler by Honeywell, H/SCHED by Haverly Systems, and SIMTO by M3 Technology. It is desirable for the planning models and the scheduling models to be consistent. Even so, there is no guarantee that the production plan can be converted into an equivalent production schedule. One weakness of this approach is that production planning and production scheduling are performed as two separate sequential steps. The optimization model used for raw material valuation and selection decisions does not reflect scheduling considerations. This can limit the quality of the solution obtained from this optimization model. When the scheduling considerations have a significant impact on the purchase and sales decisions, the absence of these factors in the optimization model can lead to a non-optimal overall solution. Thus, it is desirable to optimize a combination of several or all of these activities as one unified activity.
Notable publications on the topic of developing models for scheduling problems include the following: (1) R. Karuppiah, K. C. Furman, and I. E. Grossmann, “Global Optimization for Scheduling Refinery Crude Oil Operations,” Computers & Chemical Engineering 32, 2745-2766 (2008); (2) S. Mouret, I. E. Grossmann, and P. Pestiaux, “A Novel Priority-Slot Based Continuous-Time Formulation for Crude-Oil Scheduling Problems,” Ind. Eng. Chem. Res. 48, 8515−8528 (2009). In both of these publications, the vessel schedule (or the transportation schedule) and the raw material purchase decisions are given as input. Thus, these approaches do not apply to the simultaneous solution of raw material selection, transportation scheduling, and production scheduling.